A Two-Stage Distributionally Robust Coordinated Dispatch for Integrated Electricity and Natural-gas Energy Systems Considering Uncertainty of Wind Power

Xiao, Xingquan; Shui, Yue; Gao, Hongjun; Liu, Junyong; Chen, Qian; Li, Ting; Liu, Ying; Ouyang, Xuan

doi:10.1088/1757-899x/366/1/012016

Cited by 5 publications

(3 citation statements)

References 9 publications

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“…where η PtG and η EB represent the conversion efficiency of PtG and EB. In this paper, η MT , η gas , η PtG , and η EB are equal to 0.9, 0.85, 0.85, and 0.8, respectively [12,[34][35][36][37].…”

Section: Two-stage Day-ahead Ed For the Integratedmentioning

confidence: 99%

Robust Day-Ahead Dispatch for Integrated Power-Heat-Gas Microgrid considering Wind Power Uncertainty

Liu

Chen

et al. 2020

Mathematical Problems in Engineering

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Wind power generation has been widely deployed in the modern power system due to the issues of energy crisis and environment pollution. Meanwhile, the microgrid is gradually regarded as a feasible way to connect and accommodate the distributed wind power generations. Recently, more research studies also focus on incorporating various energy systems, for example, heat and gas into the microgrid in terms of satisfying different types of load demands. However, the uncertainty of wind power significantly impacts the economy of the integrated power-heat-gas microgrid. To deal with this issue, this paper presents a two-stage robust model to achieve the optimal day-ahead economic dispatch strategy considering the worst-case wind power scenarios. The first stage makes the initial day-ahead dispatch decision before the observation of uncertain wind power. The additional adjustment action is made in the second stage once the wind power uncertainty is observed. Based on the duality theory and Big-M approach, the original second-stage problem can be dualized and linearized. Therefore, the column-and-constraint generation algorithm can be further implemented to achieve the optimal day-ahead economic dispatch strategy for the integrated power-heat-gas microgrid. The experimental results indicate the effectiveness of the presented approach for achieving operation cost reduction and promoting wind power utilization. The robustness and the economy of the two-stage robust model can be balanced, of which the performances significantly outperform those of the single-stage robust model and the deterministic model.

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Section: Two-stage Day-ahead Ed For the Integratedmentioning

confidence: 99%

Robust Day-Ahead Dispatch for Integrated Power-Heat-Gas Microgrid considering Wind Power Uncertainty

Liu

Chen

et al. 2020

Mathematical Problems in Engineering

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“…generate constraints based on, e.g., identification of worstcase scenarios [157], Benders cuts [151], or using columnand-constraint generation [153], [156]. We also note that the method for robust co-optimization proposed in [154] uses ADMM to facilitate optimization with limited information exchange.…”

Section: Uncertainty Management In Gas-electric Energy Systemsmentioning

confidence: 99%

“…Other approaches use interval optimization [152] or draw on robust optimization techniques [64], [153]- [158]. Most of these studies consider operational scheduling, and some include emerging power-to-gas technologies [154], [159]- [161] or expansion planning [64], [156], [162].…”

Section: Uncertainty Management In Gas-electric Energy Systemsmentioning

confidence: 99%

An Uncertainty Management Framework for Integrated Gas-Electric Energy Systems

Roald¹,

Sundar²,

Zlotnik³

et al. 2020

Preprint

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In many parts of the world, electric power systems have seen a significant shift towards generation from renewable energy and natural gas. Because of their ability to flexibly adjust power generation in real time, gas-fired power plants are frequently seen as the perfect partner for variable renewable generation. However, this reliance on gas generation increases interdependence and propagates uncertainty between power grids and gas pipelines, and brings coordination and uncertainty management challenges. To address these issues, we propose an uncertainty management framework for uncertain, but bounded gas consumption by gas-fired power plants. The admissible ranges are computed based on a joint optimization problem for the combined gas and electricity networks, which involves chance-constrained scheduling for the electric grid and a novel robust optimization formulation for the natural gas network. This formulation ensures feasibility of the integrated system with a high probability, while providing a tractable numerical formulation. A key advance with respect to existing methods is that our method is based on a physically accurate, validated model for transient gas pipeline flows. Our case study benchmarks our proposed formulation against methods that ignore how reserve activation impacts the fuel use of gas power plants, and only consider predetermined gas consumption. The results demonstrate the importance of considering uncertainty to avoid operating constraint violations and curtailment of gas to the generators.

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Stochastic vs. deterministic scheduling of a combined natural gas and power system with uncertain wind energy

Ryan

2019

International Journal of Electrical Power & Energy Systems

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A Two-Stage Distributionally Robust Coordinated Dispatch for Integrated Electricity and Natural-gas Energy Systems Considering Uncertainty of Wind Power

Cited by 5 publications

References 9 publications

Robust Day-Ahead Dispatch for Integrated Power-Heat-Gas Microgrid considering Wind Power Uncertainty

Robust Day-Ahead Dispatch for Integrated Power-Heat-Gas Microgrid considering Wind Power Uncertainty

An Uncertainty Management Framework for Integrated Gas-Electric Energy Systems

Stochastic vs. deterministic scheduling of a combined natural gas and power system with uncertain wind energy

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